Sustainability and design of sustainable technologies have become an important priority for cities given the unprecedented level of resource demand—water, energy, transit, healthcare, public safety—to most if not every service that makes a city attractive and desirable. At the same time, digital reification of the cyber-physical world has been possible with widespread penetration of sensing and monitoring technologies. These two important catalysts have fuelled significant interest and cross organizational collaboration among researchers, industries, urban planners, and government. Research has focused on leveraging information from such digital reification of cyber-physical world to help manage various services more efficiently.
Real-world deployments of smart meters are designed for utility billing and some basic analysis requirement, but many of them are not suitable for consumption disaggregation. Smart meters transmit consumption readings using wireless protocols, which consume battery and have dependency on physical environments. Although the meters can sample at a rate even higher than 1 MHz, many existing deployments have chosen to accumulate data at 15 min or even longer ( 1/900 Hz or longer) intervals to ensure reliable data transmission. However, physical environment may still affect the data transmission.
Research on disaggregating electricity or water load has been conducted on smart meter readings with fine granularity (mainly between 1 Hz˜1 MHz). Existing approaches identify appliances/fixtures based on analyzing steady state or transient state change in real-time consumption.